Apparatus and method for estimating bio-information

ABSTRACT

An apparatus for non-invasively estimating bio-information is provided. According to one exemplary embodiment, the apparatus may include a bio-signal acquirer configured to acquire a bio-signal; and a processor configured to extract a plurality of characteristic points from the bio-signal, determine internally dividing points of the plurality of characteristic points, and extract feature values from the bio-signal based on the internally dividing points to perform bio-information estimation.

CROSS-REFERENCE TO RELATED APPLICATION(S)

This application claims priority from Korean Patent Application No.10-2017-0116935, filed on Sep. 13, 2017 in the Korean IntellectualProperty Office, the disclosure of which is incorporated herein byreference in its entirety.

BACKGROUND 1. Field

Apparatuses and methods consistent with exemplary embodiments relate tonon-invasively estimating bio-information.

2. Description of Related Art

Research on information technology (IT)-medical convergence technology,in which IT and medical technology are combined, is being recentlycarried out to address the aging population structure, rapid increase inmedical expenses, and shortage of specialized medical service personnel.In particular, monitoring of a health status of a human body is notlimited to being performed only at a fixed place, such as a hospital,but is expanded to a mobile healthcare sector for monitoring a user'shealth status at any time and any place in daily life at home andoffice. Electrocardiography (ECG), photoplethysmogram (PPG), andelectromyography (EMG) signals are examples of bio-signals that indicatethe individual's health condition. A variety of signal sensors are beingdeveloped to measure such signals in daily life. Especially, in the caseof a PPG sensor, it is possible to estimate blood pressure of a humanbody by analyzing a form of pulse wave that reflects a cardiovascularstate.

According to a PPG bio-signal related research, the whole PPG signal isa summation of a propagation wave propagating from the heart toperipheral parts of a body and reflection waves returning from theperipheral parts of the body. It is known that information to be used toestimate blood pressure can be acquired by extracting various featuresrelated to propagation waves or reflection waves.

SUMMARY

According to an aspect of an exemplary embodiment, there is provided anapparatus for estimating bio-information, including: a bio-signalacquirer configured to acquire a bio-signal; and a processor configuredto extract a plurality of characteristic points from the bio-signal,determine internally dividing points of the plurality of characteristicpoints, and extract feature values from the bio-signal based on theinternally dividing points to perform bio-information estimation.

The processor may include an internally dividing point calculatorconfigured to apply weights respectively to time values of the pluralityof characteristic points and calculate the internally dividing points ofthe plurality of characteristic points based on the time values to whichthe weights are applied.

The internally dividing point calculator may be further configured tocalculate the internally dividing points of the plurality ofcharacteristic points based on a sum of the weights.

The internally dividing point calculator may be further configured toapply the weights respectively to the time values based on amplitudevalues of the plurality of characteristic points.

The internally dividing point calculator may be further configured tocalculate the weights based on differences between first amplitudes at aplurality of points in a derivative signal of the bio-signal and asecond amplitude at a predetermined point in the derivative signal, andwherein the plurality of points in the derivative signal may correspondto the plurality of characteristic points extracted from the bio-signal.

The processor may include a bio-information estimator configured toestimate bio-information comprising at least one of blood pressure,vascular age, arterial stiffness, aortic pressure waveform, stressindex, and fatigue based on the extracted feature values.

The processor may include a characteristic point extractor configured toextract, as the plurality of characteristic points, at least one ofpoints associated with component pulses constituting the bio-signal, apoint at which an amplitude has a maximum value in a systolic region ofthe bio-signal, and an area of the bio-signal.

The characteristic point extractor may be further configured todetermine local minimum points in a second derivative signal of thebio-signal as the points associated with the component pulses.

The processor may further include a feature extractor configured toextract the feature values based on at least one of a ratio of the areaof the bio-signal to an amplitude value at the point at which anamplitude has the maximum value in the systolic region of the bio-signaland a difference in time value between the internally dividing pointsacquired from each of the systolic region and a diastolic region of thebio-signal.

The bio-signal acquirer may include a photoplethysmogram (PPG) sensorconfigured to emit a light to an object and acquire a PPG signal bydetecting the light reflected or scattered from the object.

The apparatus may further include a communication interface configuredto receive a PPG signal from an external device and transmit the PPGsignal to the bio-signal acquirer.

The bio-signal acquirer may include a light source configured to emit alight to an object and a detector configured to detect the lightscattered or reflected from the object, and wherein the bio-signalacquirer may acquire the bio-signal from the light detected by thedetector.

According to an aspect of another exemplary embodiment, there isprovided a method of estimating bio-information, including: acquiring abio-signal; extract a plurality of characteristic points from thebio-signal; determining internally dividing points of the plurality ofcharacteristic points; and extracting feature values from the bio-signalbased on the internally dividing points to perform bio-informationestimation.

The determining the internally dividing points may include applyingweights respectively to time values of the plurality of characteristicpoints and calculating the internally dividing points of the pluralityof characteristic points based on the time values to which the weightsare applied.

The determining the internally dividing points may include calculatingthe internally dividing points of the plurality of characteristic pointsbased on a sum of the weights.

The determining the internally dividing points may include applying theweights respectively to the time values based on amplitude values of theplurality of characteristic points.

The determining the internally dividing points may include applying theweights respectively to the time values based on differences betweenfirst amplitudes at a plurality of points in a derivative signal of thebio-signal and a second amplitude at a predetermined point in thederivative signal, and wherein the plurality of points in the derivativesignal may correspond to the plurality of characteristic pointsextracted from the bio-signal.

The method may further include estimating the bio-information, whichincludes at least one of blood pressure, vascular age, arterialstiffness, aortic pressure waveform, stress index, and fatigue, based onthe extracted feature values.

The method may further include extracting, as the plurality ofcharacteristic points, at least one of points associated with componentpulses constituting the bio-signal, a point at which an amplitude has amaximum value in a systolic region of the bio-signal, and an area of thebio-signal.

The extracting of the characteristic points may include determininglocal minimum points in a second derivative signal of the bio-signal asthe points associated with the component pulses.

The extracting the feature values may include extracting the featurevalues based on at least one of a ratio of the area of the bio-signal toan amplitude value at the point at which an amplitude has the maximumvalue in the systolic region of the bio-signal and a difference in timevalue between the internally dividing points acquired from each of thesystolic region and a diastolic region of the bio-signal.

According to an aspect of another exemplary embodiment, there isprovided a blood pressure monitoring device, including: a light emitterconfigured to emit a light to a subject; a light detector configured todetect the light that is scattered, deflected, or reflected from thesubject to obtain a pulse wave signal from the detected light; aprocessor configured to extract a plurality of characteristic pointsfrom the pulse wave signal, determine amplitude values corresponding tothe plurality of characteristic points from the pulse wave signal,determine an internally dividing point of the plurality ofcharacteristic points based on the amplitude values and the plurality ofcharacteristic points, and determine a blood pressure of the subjectbased on the internally dividing point of the pulse wave signal.

The processor may be further configured to: extract a first time pointT₁ and a second time point T₂ from the pulse wave signal, as theplurality of characteristic points, when the pulse wave signal comprisesa first component pulse wave that has a maximum amplitude at the firsttime point T₁, and a second component pulse wave that has a maximumamplitude at the second time point T₂; determine a first amplitude P₁and a second amplitude P₂ of the pulse wave signal corresponding to thefirst time point T₁ and the second time point T₂, respectively; anddetermine the internally dividing point based on the first time pointT₁, the second time point T₂, the first amplitude P₁, and the secondamplitude P₂.

The processor may be further configured to: extract a first time pointT₁ and a maximum time point T_(max) from the pulse wave signal, as theplurality of characteristic points, when the pulse wave signal comprisesa first component pulse wave that has a maximum amplitude at the firsttime point T₁, and the pulse wave signal has a maximum amplitude P_(max)at the maximum time point T_(max); determine a first amplitude P₁ of thepulse wave signal corresponding to the first time point T₁; anddetermine the internally dividing point based on the first time pointT₁, the maximum time point T_(max), the first amplitude P₁ and themaximum amplitude P_(max).

The processor may be further configured to: extract a third time pointT₃ and a fourth time point T₄ from the pulse wave signal, as theplurality of characteristic points, when the pulse wave signal comprisesa third component pulse wave that has a maximum amplitude at the thirdtime point T₃, and a fourth component pulse wave that has a maximumamplitude at the fourth time point T₄; determine a third amplitude P₃and a fourth amplitude P₄ of the pulse wave signal corresponding to T3and T4, respectively; and determine the internally dividing point basedon the third time point T₃, the fourth time point T₄, the thirdamplitude P₃, and the fourth amplitude P₄, in response to the fourthamplitude P₄ being greater than the third amplitude P₃.

The processor may be further configured to: extract a third localminimum point T_(local3) and a fourth local minimum point T_(local4)from a second derivative signal of the pulse wave signal; extract, fromthe second derivative signal, a third local maximum point L₃ thatappears prior to the third local minimum point T_(local3), and a fourthlocal maximum point L₄ that appears between the third local minimumpoint T_(local3) and the fourth local minimum point T_(local4);determine a first difference W₁ between an amplitude at the third localminimum point T_(local3) and an amplitude at the fourth local maximumpoint L₄; determine a second difference W₂ between the amplitude at thefourth local maximum point L₄ and an amplitude at the fourth localminimum point T_(local4); and determine the internally dividing pointbased on the third local minimum point T_(local3), the fourth localminimum point T_(local4), the first difference w1, and the firstdifference w2.

The processor may be further configured to: extract a third localminimum point T_(local3) and a fourth local minimum point T_(local4)from a second derivative signal of the pulse wave signal; extract, fromthe second derivative signal, a third local maximum point L₃ thatappears prior to the third local minimum point T_(local3), and a fourthlocal maximum point L₄ that appears between the third local minimumpoint T_(local3) and the fourth local minimum point T_(local4);determine a first difference W₁ between an amplitude at the third localmaximum point L₃ and an amplitude at the third local minimum pointT_(local3); determine a second difference W₂ between the amplitude atthe third local maximum point L₃ and the amplitude at the fourth localminimum point T_(local4); and in response to the first difference W₁being less than a predetermined threshold value, determine theinternally dividing point based on the third local minimum pointT_(local3), the fourth local minimum point T_(local4), the firstdifference w1, and the first difference w2.

BRIEF DESCRIPTION OF THE DRAWINGS

The above and/or other aspects will be more apparent by describingcertain exemplary embodiments, with reference to the accompanyingdrawings, in which:

FIG. 1 is a block diagram illustrating an apparatus for estimatingbio-information according to one exemplary embodiment.

FIG. 2 is a block diagram illustrating an apparatus for estimatingbio-information according to another exemplary embodiment.

FIG. 3 is a block diagram illustrating a processor according to theexemplary embodiments of FIGS. 1 and 2.

FIGS. 4A, 4B, and 4C are diagrams for describing an exemplary embodimentin which characteristic points are extracted from a bio-signal.

FIGS. 5A, 5B, 5C, 5D, and 5E are diagrams for describing an exemplaryembodiment in which internal dividing points are calculated using thecharacteristic points of the bio-signal.

FIGS. 6A, 6B, and 6C are flowcharts illustrating a method of estimatingbio-information according to one exemplary embodiment.

FIGS. 7A, 7B, 7C, and 7D are diagrams for describing a wearable deviceaccording to one exemplary embodiment.

DETAILED DESCRIPTION

Exemplary embodiments are described in greater detail below withreference to the accompanying drawings.

In the following description, like drawing reference numerals are usedfor like elements, even in different drawings. The matters defined inthe description, such as detailed construction and elements, areprovided to assist in a comprehensive understanding of the exemplaryembodiments. However, it is apparent that the exemplary embodiments canbe practiced without those specifically defined matters. Also,well-known functions or constructions are not described in detail sincethey would obscure the description with unnecessary detail.

It will be understood that, although the terms first, second, etc. maybe used herein to describe various elements, these elements should notbe limited by these terms. These terms are only used to distinguish oneelement from another. Also, the singular forms are intended to includethe plural forms as well, unless the context clearly indicatesotherwise. In the specification, unless explicitly described to thecontrary, the word “comprise” and variations such as “comprises” or“comprising,” will be understood to imply the inclusion of statedelements but not the exclusion of any other elements. Terms such as “ .. . unit” and “module” denote units that process at least one functionor operation, and they may be implemented by using hardware, software,or a combination of hardware and software.

Expressions such as “at least one of,” when preceding a list ofelements, modify the entire list of elements and do not modify theindividual elements of the list.

FIG. 1 is a block diagram illustrating an apparatus for estimatingbio-information according to one exemplary embodiment. The apparatus 100for estimating bio-information of the present exemplary embodiment maybe implemented as a hardware device to be mounted in a terminal, such asa smartphone, a tablet personal computer (PC), a desktop PC, a notebookPC, or the like, or an independent hardware device. When the apparatus100 is implemented as an independent hardware device, the apparatus 100may have the form of a wearable device that a user (e.g., an object OBJ)can easily measure bio-information while carrying the device. Forexample, the hardware device may be implemented as a wearable device ofa wristwatch type, a bracelet type, a wristband type, a ring type, aglass type, or a hairband type. However, the type of wearable device isnot limited to the above examples, and the wearable device may bemodified according to various purposes, for example, it may bemanufactured as a fixed type for utilizing bio-information in a medicalinstitution for measurement and analysis.

Referring to FIG. 1, the apparatus 100 for estimating bio-informationincludes a bio-signal acquirer 110 and a processor 120.

The bio-signal acquirer 110 may acquire a bio-signal from an object OBJas shown in FIG. 1 and transmit the acquired bio-signal to the processor120. In this case, the bio-signal may be a photoplethysmogram (PPG)signal (hereafter referred to as a “pulse wave signal”). However, thebio-signal is not limited thereto and may include various bio-signals,such as an electrocardiography (ECG) signal, a PPG signal, anelectromyography (EMG) signal, and the like, which can be modeled by aplurality of waveform components.

For example, the bio-signal acquirer 110 may include a spectrometer or aPPG sensor configured to measure a PPG signal. The PPG sensor mayinclude a light source configured to emit light to the object OBJ and adetector configured to measure a PPG signal by detecting light scatteredor reflected from tissues of the irradiated object OBJ. In this case,the light source may include at least one of a light emitting diode, alaser diode, and a phosphor, but is not limited thereto. The detectormay include a photodiode.

The processor 120 may generate a control signal to drive the bio-signalacquirer 110. Upon receiving the control signal from the processor 120,the bio-signal acquirer 110 may emit a light to the object OBJ andreceive the light that is reflected from the OBJ. The bio-signal acquire110 may acquire a pulse wave signal (i.e., a PPG signal) from thereceived light. The object is a living body which can be in touch withor adjacent to the PPG sensor and may be a part of a human body which iseasy to measure a PPG signal. For example, the object OBJ may be an areaof a wrist surface adjacent to a radial artery and may include an upperpart of a wrist where venous blood or capillary blood passes. When apulse wave is measured at a skin surface of the wrist under which theradial artery passes, the influence of external factors, such as thethickness of the skin tissue inside the wrist, which cause a measurementerror can be relatively small. However, the object OBJ is not limited tothe above examples, and may be a peripheral region of a human body, suchas a finger, a toe, or the like, which is a region having a high bloodvessel density in the human body.

When acquiring the bio-signal, the bio-signal acquirer 110 may performpreprocessing on the bio-signal, such as filtering for removing noisefrom the acquired bio-signal, amplification of the bio-signal, orconverting the bio-signal into a digital signal.

When the processor 120 receives a request for bio-signal estimation fromthe user, the processor 120 may generate a control signal to control thebio-signal acquirer 110, and transmit the control signal to thebio-signal acquirer 110. In addition, the processor 120 may receive thebio-signal from the bio-signal acquirer 110 and acquire bio-informationby analyzing the received bio-signal. In this case, the bio-informationmay include a blood pressure, vascular age, arterial stiffness, aorticpressure waveform, stress index and fatigue, but is not limited thereto.

When the processor 120 receives the bio-signal from the bio-signalacquirer 110, the processor 120 may extract features necessary forbio-information estimation by analyzing a waveform of the receivedbio-signal. To this end, the processor 120 may extract a plurality ofcharacteristic points from the received bio-signal and extract thefeatures using the extracted characteristic points.

For example, the processor 120 may extract points associated with aplurality of component pulses constituting the waveform of the entirebio-signal as the characteristic points. In addition, the processor 120may calculate internally dividing points of characteristic points. Theprocessor 120 may use any one or any combination of the characteristicpoints and the internally dividing points to extract features forbio-information estimation. As such, the internally dividing point iscalculated from the characteristic points initially extracted from thebio-signal and is used along with the characteristic points to extractadditional features that may be used to perform bio-informationestimation. Accordingly, it may be possible to obtain a more accuratefeature even when the initially extracted characteristic points areextracted from an instable waveform under a non-ideal environment, suchas motion noise or sleep.

FIG. 2 is a block diagram illustrating an apparatus for estimatingbio-information according to another exemplary embodiment.

Referring to FIG. 2, an apparatus 200 for estimating bio-informationincludes a bio-signal acquirer 110, a processor 120, a communicationinterface 210, an output interface 220, and a storage 230.

The bio-signal acquirer 110 may acquire a bio-signal of an object froman external device 250. For example, the bio-signal acquirer 110 mayacquire a bio-signal from the external device 250 through thecommunication interface 210 without being equipped with a bio-signalmeasurement sensor, such as a PPG sensor. Alternatively, when thebio-signal acquirer 110 is equipped with the bio-signal measurementsensor, such as a PPG sensor, the bio-signal acquirer 110 mayselectively use a method of acquiring a bio-signal from the externaldevice 250 under the control of the processor 120 or acquiring abio-signal by directly driving the bio-signal measurement sensor.

The bio-signal acquirer 110 may perform a preprocessing operation toremove noise from the bio-signal received from the external device 250and convert the bio-signal into a digital signal, and then may transmitthe processed bio-signal to the processor 120.

The processor 120 may generate a control signal to control thebio-signal acquirer 110 in order to acquire the bio-signal. In addition,when the bio-signal is to be acquired from the external device 250, theprocessor 120 may control the communication interface 210 to beconnected to the external device 250.

The apparatus 200 may be connected to the external device 250 throughthe communication interface 213, using access information of theexternal device 250 that is included in the control signal. Once theapparatus 200 is connected to the external device 250, the apparatus 200210 may receive the bio-signal from the external device 250 and thentransmit the bio-signal to the bio-signal acquirer 110, through thecommunication interface 210. In this case, the external device 250 mayinclude a bio-signal measurement sensor to directly measure a bio-signalfrom the object, or may be a device that receives a bio-signal from abio-signal measurement device and stores the received bio-signal.

In particular, the communication technology may include a Bluetoothcommunication, a Bluetooth low energy communication, a near fieldcommunication (NFC), a wireless local area network (WLAN) communication,a ZigBee communication, an infrared data association (IrDA)communication, a Wi-Fi direction communication, an ultra-wideband (UWB)communication, Ant+ communication, a Wi-Fi communication, and a mobilecommunication technology, but is not limited thereto.

When receiving the bio-signal from the bio-signal acquirer 110, theprocessor 120 may analyze the bio-signal to extract characteristicpoints and extract features that may be necessary for bio-signalestimation using the extracted characteristic points. In this case, whena waveform of the bio-signal exhibits a non-ideal and unstable form, theprocessor 120 may calculate internally dividing points using theextracted characteristic points and use the calculated internallydividing points along with the characteristic points to extractfeatures.

When the features are extracted, the processor 120 may estimatebio-information using the extracted feature. In this case, thebio-information may be estimated using a previously constructedbio-information estimation model.

The output interface 220 may output and provide the acquired bio-signalinformation and various processing results of the processor 120. Theoutput interface 220 may provide the information to the user throughvarious visual/non-visual methods using a display module, a speaker, anda haptic device mounted in the device.

For example, when a blood pressure of the user is estimated, the outputinterface 220 may output the estimated blood pressure to the user usingvarious visual methods, such as a color, a thickness of a line, a font,and the like, based on whether the estimated blood pressure is within orout of a normal range. Alternatively, the estimated blood pressure maybe output by voice or through a non-visual method in which vibration ortactile sensation is changed according to the abnormality of the bloodpressure. Alternatively, when it is determined that the estimated bloodpressure is abnormal when compared with the recent history ofmeasurement, the user may be warned or advised about actions to be takenby providing, for example, cautionary food information or informationabout a hospital to be reserved.

The storage 230 may store various pieces of reference informationrequired for bio-information estimation, the obtained bio-signal, theextracted characteristic points and internally dividing points, theextracted features, bio-information estimation results, and the like. Inthis case, the various pieces of reference information required forbio-information estimation may include user information, such as an age,sex, occupation, current health status, and the like, and thebio-information estimation model information, but is not limitedthereto. The storage 230 may include a storage medium of at least onetype of a flash memory type, a hard disk type, a multimedia card microtype, a card-type memory (e.g., Secure Digital or eXtreme Digitalmemory, etc.) a random access memory (RAM), a static random accessmemory (SRAM), a read-only memory (ROM), an electrically erasableprogrammable read-only memory (EEPROM), a programmable read-only memory(PROM), a magnetic memory, a magnetic disk, and an optical disk.

Meanwhile, when there is a request from the external device 250 throughthe communication interface 210, the processor 120 may request theexternal device 250 to estimate bio-information by transmittinginformation about at least one of the extracted characteristic points,the internally dividing points, and the extracted feature to theexternal device 250. However, aspects of the present disclosure are notlimited thereto, and when the external device 250 is a device having arelatively better computing performance and equipped with abio-information estimation function, the external device 250 may requestthe bio-information estimation by transmitting the characteristicpoints, internally dividing points, or feature information.

FIG. 3 is a block diagram illustrating the processor according to theexemplary embodiments of FIGS. 1 and 2. FIGS. 4A to 4C are diagrams fordescribing an exemplary embodiment in which characteristic points areextracted from a bio-signal. FIGS. 5A to 5E are diagrams for describingan exemplary embodiment in which internal dividing points are calculatedusing the characteristic points of the bio-signal.

An exemplary embodiment in which features necessary for bio-informationestimation are extracted through characteristic point extraction,internally dividing point calculation, and the calculated internallydividing points will be described with reference to FIGS. 3 to 5E.Hereinafter, for convenience of description, it will be assumed that anacquired bio-signal is a pulse wave signal and the bio-information to beestimated is blood pressure.

As shown in FIG. 3, a processor 300 includes a characteristic pointextractor 310, an internally dividing point calculator 320, a featureextractor 330, and a bio-information estimator 340.

The characteristic point extractor 310 may extract characteristic pointsusing the bio-signal acquired from an object. For example, thecharacteristic point extractor 310 may extract points associated withcomponent pulses constituting the bio-signal as characteristic points.

Generally, the pulse wave signal acquired from the object may be asummation of a propagation wave propagating from the heart to peripheralparts of a body and reflection waves returning from the peripheral partsof the body. FIG. 4A illustrates a pulse wave signal 40 which is asummation of five component pulses 41, 42, 43, 44, and 45. Wheninformation about points associated with each of the component pulses41, 42, 43, 44, and 45, for example, time and amplitude information maybe extracted as characteristic points and the extracted characteristicpoints are appropriately combined, a feature with high correlation withblood pressure may be extracted. Generally, up to third component pulsesare mainly used to estimate blood pressure. Subsequent pulses may not beobserved because it may be difficult to detect the subsequent pulses dueto noise. Also, the subsequent pulses may have low correlation withblood pressure estimation.

FIG. 4B illustrates an example of extracting points associated withcomponent pulses as characteristic points from a pulse wave signal usinga second derivative signal of a bio-signal. Referring to FIG. 4B, when abio-signal is acquired as shown in (1) BIO-SIGNAL, the characteristicpoint extractor 310 may derive a second derivative signal bydifferentiating the bio-signal as shown in (2) SECOND DERIVATIVE SIGNAL,search for local minimum points from the derived second derivate signalas shown in (3) TIME INFORMATION OF LOCAL MINIMUM POINTS, and extracttime points T₁, T₂, and T₃ corresponding to the local minimum points asthe characteristic points, as shown in (4) AMPLITUDE INFORMATION OFBIO-SIGNAL. In addition, the characteristic point extractor 310 mayextract, from the entire bio-signal, amplitudes P₁, P₂, and P₃corresponding to the time points T₁, T₂, and T₃ extracted from thederivative signal as characteristic points. The local minimum point mayrefer to a specific point of a part of the second derivative signalwhere the signal decreases and increases again, that is, a point havinga downwardly convex shape. For example, the local minimum point mayrefer to a point of a graph where the graph changes from increasing todecreasing, or the smallest value of the graph within a given range.

In another example, the characteristic point extractor 310 may extract apoint in a predetermined region of the bio-signal 40 where the amplitudeis the maximum as an additional characteristic point, as shown in FIG.4C. In this case, the predetermined region of the bio-signal 40 refersto a systolic phase of the blood pressure from the beginning of thebio-signal 40 to the point of the dicrotic notch (DN). The dicroticnotch may refer to an acute drop followed by a rise in blood pressurepulse curves, which appears subsequent to a systolic peak. For example,a position where the bio-signal 40 is curved or bulged downward betweentime points T₂ and T₃ may correspond to the dicrotic notch. When thebio-signal 40 is acquired, the characteristic point extractor 310 mayextract time points T₁, T₂, and T₃ and amplitudes P₁, P₂, and P₃ fromeach of the three component pulses 41, 42, and 43 constituting thebio-signal 40 as characteristic points, and extract a time point T_(max)and an amplitude P_(max) at a point where the systolic phase of theblood pressure as additional characteristic points. In this case, asdescribed above, the characteristic point extractor 310 may derive asecond derivative signal and extract characteristic points by searchingfor local minimum points of the second derivative signal.

In another example, the characteristic point extractor 310 may extractan area S_(area) of the bio-signal waveform, for example, the whole areaor a partial area as characteristic points. At this time, the partialarea may mean the area of the bio-signal waveform corresponding to atime region from the beginning to a predetermined ratio (e.g., 70%)based on a time axis of the bio-signal waveform.

However, examples of the characteristic point extraction of thebio-signal are not limited to the above description, and thecharacteristic points may be extracted using other various methods.

When the characteristic points are extracted from the bio-signal asdescribed above, the feature extractor 330 may combine the extractedcharacteristic points to extract features for bio-informationestimation. However, if only the points associated with the componentpulses are extracted as described, it may be difficult to extract stablecharacteristic points and feature when noise is contained in thebio-signal waveform or an unstable waveform occurs in a movingenvironment. Therefore, according to the present exemplary embodiment,the internally dividing point calculator 320 may calculate internallydividing points using the characteristic points extracted by thecharacteristic point extractor 310, thereby allowing the calculatedinternally dividing points to be used along with the extractedcharacteristic points in feature extraction.

FIGS. 5A and 5B are diagrams illustrating examples in which theinternally dividing point calculator 320 calculates an internallydividing point in a systolic region. The systolic region may refer to aregion between the beginning of an acquired pulse wave signal 51 and thedicrotic notch (DN).

Referring to FIG. 5A, the internally dividing point calculator 320 maycalculate an internally dividing point (T_(sys), P_(sys)) between twocharacteristic points (T₁, P₁) and (T₂, P₂) using the two characteristicpoints (T₁, P₁) and (T₂, P₂) associated with a component pulse extractedfrom the systolic region by the characteristic point extractor 310. Forexample, the internally dividing point calculator 320 may apply weightsa and b respectively to each time value T₁ and T₂ of the twocharacteristic points (T₁, P₁) and (T₂, P₂), and calculate theinternally dividing point T_(sys) using each of the time values aT₁, bT₂to which the weights are applied. For example, the internally dividingpoint calculator 320 may obtain the internally dividing point T_(sys) bysumming the time values aT₁ and bT₂ to which the weights are applied anddividing the sum of the time values by the sum of the weights. Each ofthe weights a and b may be determined based on the amplitudes P₁ and P₂of the respective characteristic points, and the internally dividingpoint T_(sys) may be calculated as shown in Equation 1:T _(sys)=(P ₁ ×T ₁ +P ₂ ×T ₂)/(P ₁ +P ₂)  (1)

However, the exemplary embodiment is not limited to the above examples,and the weight to be applied to each of the time points may be anarbitrary constant predefined through a preprocessing operation. Assuch, when the internally dividing point time T_(sys) is determined, itis possible to extract the amplitude P_(sys) at a point of thebio-signal corresponding to T_(sys).

Referring to FIG. 5B, the internally dividing point calculator 320 maycalculate an internally dividing point between two characteristic points(T₁, P₁) and (T_(max), P_(max)) using the two characteristic points (T₁,P₁) and (T_(max), P_(max)) extracted from a systolic region of thebio-signal 51. Similarly, the internally dividing point calculator 320may apply weights respectively to each of the time values T₁ and T_(max)of the two characteristic points (T₁, P₁) and (T_(max), P_(max)) andcalculate an internally dividing point T_(sys) using each of the timevalues to which the weights are applied. For example, the internallydividing point T_(sys) may be calculated as shown in Equation 2:T _(sys)=(P ₁ ×T ₁ +P _(max) ×T _(max))/(P ₁ +P _(max))  (2)

The exemplary embodiment of FIG. 5B is useful when a waveform of thebio-signal 51 is not ideal and exhibits instability. For example, in thecase of an abnormal waveform, a waveform component corresponding to thesecond characteristic point (T₂, P₂) may not be accurately observed. Inthis case, instead of the second characteristic point (T₂, P₂), acharacteristic point (T_(max), P_(max)) at which the amplitude is themaximum in the systolic region may be used to obtain an internallydividing point (T_(sys), P_(sys)) robust to the abnormal waveform. Inaddition, in a case where a waveform of the bio-signal is unstable, avalue of P₁ of the first characteristic point in an environment wherecharacteristic points are continuously measured may be suddenly observedas a very small value. Even in this case, if an amplitude value P_(max)at a point where the amplitude is the maximum in the systolic region ismaintained constant, by giving a weight based on the amplitude values P₁and P_(max), a robust internally dividing point (T_(sys), P_(sys)) maybe obtained in spite of the instability of the characteristic point (T₁,P₁).

FIGS. 5C to 5E are diagrams for describing an exemplary embodiment inwhich an internally dividing point in the diastolic region iscalculated. The diastolic region may refer to a region of a bio-signalafter dicrotic notch (DN).

Referring to FIG. 5C, the characteristic point extractor 310 may extracta point (T₃, P₃), which is a point associated with the third componentpulse, as a representative characteristic point in the diastolic regionof a pulse wave signal 52. This characteristic point increases ininstability relative to a characteristic point extracted from thediastolic region due to various noises generated. According to thepresent exemplary embodiment, the internally dividing point calculator320 may calculate an internally dividing point by utilizing acharacteristic point of another component pulse in the systolic region.

For example, as shown in FIG. 5C, when it is assumed that generally thethird component pulse associated with the characteristic point (T₃, P₃)is a waveform component having the largest maximum amplitude in thediastolic region of a bio-signal, a characteristic point (T₄, P₄)associated with a waveform component having an amplitude greater than anamplitude of the amplitude P₃, for example, a waveform component of thefourth component pulse in the diastolic region may be extracted in thecase of a specific bio-signal waveform. In this case, physiologically,the characteristic point (T₃, P₃) associated with the third componentpulse may not be given great significance. At this point, the internallydividing point calculator 320 may calculate an internally dividing point(T_(dia), P_(dia)) of the characteristic points (T₃, P₃) and (T₄, P₄)extracted from the diastolic region. The internally dividing pointcalculator 320 may apply weights respectively to each of the time pointsT₃ and T₄ based on each of the amplitudes P₃ and P₄, and calculate theinternally dividing point (T_(dia), P_(dia)) in the diastolic regionbased on the time values to which the weights are applied. For example,the internally dividing point (T_(dia), P_(dia)) may be calculated asshown in Equation 3:T _(dia)=(P ₃ ×T ₃ +P ₄ ×T ₄)/(P ₃ +P ₄)  (3)

Meanwhile, the internally dividing point calculator 320 may determinewhether a preset condition of calculating the internally dividing pointin the diastolic region is satisfied, and, when the condition issatisfied, may calculate the internally dividing point. In this case,the condition for calculating the internally dividing point in thediastolic region may be satisfied when the value of P₃ is smaller thanthe value of P₄. When it is determined that the value of P₃ is greaterthan the value of P₄, the characteristic point (T₃, P₃) extracted fromthe third component pulse may be used as is. However, the condition forcalculating the internally dividing point is not limited to the abovedescription, and the condition may include a case where a differencebetween P₃ and P₄ is not greater than an arbitrary number, a case wherea difference between P₃ and P₄ is greater than an arbitrary number, orthe like.

In another example, the internally dividing point calculator 320 maycalculate the internally dividing point based on an n-order derivativesignal of the bio-signal in the diastolic region. The characteristicpoint extractor 310 may search for local minimum points of a secondderivative signal by second order differentiating the bio-signal andextract characteristic points associated with component pulses, asdescribed above. In this case, if the bio-signal has been acquired in anon-ideal environment and thus the waveform of the bio-signal isunstable, the second derivative signal may also fluctuate unstably. Forexample, the local minimum point of the second derivative signalcorresponding to the representative characteristic point (T₃, P₃) of thediastolic region does not appear at the physiologically correctposition, and the local minimum point of the second derivative signalmay unsteadily fluctuate back and forth around the correspondingposition.

In this case, the internally dividing point calculator 320 may calculatean internally dividing point of characteristic points extracted from twolocal minimum points of the second derivative signal in order toalleviate the instability of the second derivative signal. Theinternally dividing point calculator 320 may apply a weight to each ofthe time values of the characteristic points based on a differencebetween the amplitude of each of the local minimum points of the secondderivative signal and the amplitude at a predetermined point of thesecond derivative signal, and calculate the internally dividing pointusing each of the time values to which the weights are applied, asdescribed above.

For example, referring to FIG. 5D, a difference W₁ between the amplitudeof T₃, which is a local minimum point of a diastolic region of a secondderivative signal 54, and the amplitude of a local maximum point L₄,which appears immediately before T₄, may be determined as a weight to beapplied to the time value T₃ of a characteristic point in the diastolicregion. In addition, a difference W₂ between the amplitude of T₄, whichis a local minimum point, and the amplitude of L₄, which is a localmaximum point, may be determined as a weight of the time value T₄ of acharacteristic point of the diastolic region. The time value T₃ may bereferred to as a third local minimum point given that the time value T₃is a local minimum point that thirdly appears in the diastolic region ofthe second derivative signal 54. The time value T₄ may be referred to asa fourth local minimum point given that the time value T₄ is a localminimum point that fourthly appears in the diastolic region of thesecond derivative signal 54. According to the exemplary embodiment ofFIG. 5D, the internally dividing point (T_(dia), P_(dia)) may becalculated as shown in Equation 4:T _(dia)=(W ₁ ×T ₃ +W ₂ ×T ₄)/(W ₁ +W ₂)  (4)

FIG. 5E shows an example in which differences between the amplitude ofT₃ and the amplitude of L₃ and between the amplitude of T₄ and theamplitude of L₃ are determined as weights W₁ and W₂ to be appliedrespectively to time values T3 and T4 of characteristic points of thediastolic region.

Meanwhile, the internally dividing point calculator 320 may determinewhether a condition for calculating an internally dividing point issatisfied based on at least one of the weights W₁ and W₂, which areobtained based on the second derivative signal, and when the conditionis satisfied, may calculate the internally dividing point. For example,only when the weight W₁ to be applied to the first characteristic point(T₃, P₃) in the diastolic region is smaller than a predeterminedthreshold, the internally dividing point may be calculated. If theweight W₁ is greater than or equal to the predetermined threshold, thefirst characteristic point (T₃, P₃) may be used as is without the weightW₁ being applied. However, the exemplary embodiment is not limitedthereto, and the condition for calculating the internally dividing pointmay include various conditions, such as a case where the W₂ to beapplied to the second characteristic point (T₄, P₄) in the diastolicregion is greater than a predetermined threshold.

Once the characteristic points and the internally dividing points areobtained, the feature extractor 330 may determine information to be usedin feature extraction among the obtained characteristic points andinternally dividing points, and extract features necessary forbio-information extraction by combining the determined information.

For example, it is assumed that (T₁, P₁), (T₃, P₃), (T₄, P₄), (T_(max),P_(max)), and S_(are) are extracted by the characteristic pointextractor 310. In addition, it is assumed that an internally dividingpoint (T_(sys), P_(sys)) between the characteristic points (T₁, P₁) and(T_(max), P_(max)) and an internally dividing point (T_(dia), P_(dia))between the characteristic points (T₃, P₃) and (T₄, P₄) are calculated.In this case, through an analysis of bio-signal waveform, secondderivative signal waveform, and component pulses, the feature extractor330 may determine the calculated internally dividing points (T_(sys),P_(sys)) and (T_(dia), P_(dia)), the characteristic point (T_(max),P_(max)), and S_(area) as information to be used in feature extraction.In addition, the feature extractor 330 may acquire two features f₁ andf₂ as shown in Equation 5 below by combining the determined information.f ₁ =P _(max) /S _(area)f ₂=1/(T _(dia) −T _(sys))  (5)

However, the features are merely examples, and are not limited thereto.For example, the first feature f₁ is a feature related to the cardiacoutput, and it may further include, such as, P_(max)/P_(area),P_(max)/P₃, P_(sys)/P₃, P₁/P₃, P₂/P₃, 1/T_(period), or the like. Thesecond feature f₂ is a feature related to the total peripheral vascularresistance, and it may further include 1/(T₃−T_(sys)), 1/(T₃−T_(max)),1/(T₃−T₁), 1/(T₃−T₂), P₃/P₁, P₂/P₁, or the like. Here, P_(area) denotesthe sum of amplitudes of the bio-signal for a predefined time interval(e.g. between time 0 and τ_(dur)*T_(period)). T_(period) denotes aperiod of the bio-signal. τ_(dur) denotes a predefined setting factor(0≤τ_(dur)≤1) (e.g., 0.7).

When the feature extractor 320 extracts the features, thebio-information estimator 340 may estimate bio-information using theextracted features. For example, blood pressure may be estimated byapplying the features extracted as shown in the above Equation 5 to ablood pressure estimation equation as shown in Equation 6 below.BP=A(f ₁ +wf ₂)+B  (6)

Here, BP denotes an estimated blood pressure, and A, w, and B denotearbitrary coefficients.

FIG. 6A is a flowchart illustrating a method of estimatingbio-information according to one exemplary embodiment.

FIG. 6A shows an exemplary embodiment of a method of estimatingbio-information which is performed by the apparatus 100 for estimatingbio-information according to the exemplary embodiment of FIG. 1, whichhas been described in detail with reference to FIGS. 1 to 5E, and thusthe method will be described in brief to avoid unnecessary repetition.

First, the apparatus 100 for estimating bio-information receives arequest for bio-information estimation, in operation 610. The apparatus100 may provide an interface to perform various interactions with auser. The user may request the bio-information estimation through theinterface provided by the apparatus 100.

Alternatively, the apparatus 100 may receive a request forbio-information estimation from an external device. In this case, therequest for bio-information estimation received from the external devicemay include a request for providing a bio-information estimation result.When the external device is equipped with a bio-information estimationalgorithm, the request for bio-information estimation may include arequest for providing characteristic point or feature information. Theexternal device may include a smartphone or a tablet PC that the usercarries, and the user may control the apparatus 100 through a portabledevice having superior interface performance and computing performanceto those of the apparatus 100 for bio-information estimation.

Then, the apparatus 100 acquires a bio-signal for bio-informationestimation, in operation 620. For example, the apparatus 100 may controla bio-signal measurement sensor (e.g., a PPG sensor) to measure a pulsewave signal, and acquire a pulse wave signal from an object. In anotherexample, when the apparatus 100 does not include the bio-signalmeasurement sensor, the apparatus 100 may receive a bio-signal from anexternal bio-signal measurement device.

Then, a plurality of characteristic points may be extracted from theacquired bio-signal, in operation 630. As described above, the apparatus100 may extract points associated with component pulses constituting theacquired bio-signal as the characteristic points. For example, theapparatus 100 may acquire a second derivative signal of a pulse wavesignal acquired for estimating blood pressure, and extract informationabout time and amplitude of a local minimum point of the secondderivative signal as a characteristic point associated with a componentpulse. In addition, the apparatus 100 may extract time and amplitudeinformation at a point where the amplitude is the maximum in a systolicphase of blood pressure as an additional characteristic point in orderto compensate the case where the pulse wave signal is unstable due tonoise, motion, or the like. Also, the apparatus 100 may extract thewhole area or a partial area of the pulse wave signal as an additionalcharacteristic point.

Thereafter, internally dividing points of two or more characteristicpoints are calculated, in operation 640. For example, the apparatus 100may calculate an internally dividing point for each of the systolicregion and the diastolic region of the pulse wave signal. Two timevalues extracted from the pulse wave signal may be given weights and aninternally dividing point may be calculated using the time values towhich the weights are applied. In this case, the weights may bedetermined based on the amplitude values of two characteristic points.For example, the internally dividing point may be calculated by dividingthe sum of the time values to which the weights are applied by the sumof the weights. Meanwhile, when the plurality of characteristic pointsare extracted, the apparatus 100 may check various preset conditions forcalculating an internally dividing point, and may use the extractedcharacteristic points intact when the conditions are not satisfied.

Then, the apparatus 100 extracts features necessary for bio-informationestimation using the extracted characteristic points and internallydividing points, in operation 650. In this case, the features necessaryfor bio-information estimation may be extracted by combining two or morecharacteristic points and internally dividing points as shown inEquation 5.

Hereinafter, operations 630 to 650 are described with references toFIGS. 6B and 6C in greater detail.

As shown in FIG. 6B, the apparatus 100 may extract characteristic points(T₁, P₁), (T₂, P₂), and (T_(max), P_(max)) from the systolic region ofthe pulse wave signal, in operation 630 a. In turn, the apparatus 10 maycalculate a first internally dividing point T_(sys1) according toequation 1 in operation 640 a, and may calculate a second internallydividing point T_(sys2) according to equation 2 in operation 640 b. Theapparatus 100 may perform either operation 640 a or operation 640 b, orboth of the operations 640 a and 640 b. Then, the apparatus 100 mayextract features based on the first internally dividing point T_(sys1)and the second internally dividing point T_(sys2) in operations 650 aand 650 b, respectively.

As shown in FIG. 6C, the apparatus 100 may extract characteristic points(T₃, P₃) and (T₄, P₄) from the diastolic region of the pulse wavesignal, in operation 630 b. If the apparatus 100 determines that theamplitude P₄ is greater than the amplitude P₃ in operation 640 c, theapparatus 100 may calculate a first internally dividing point T_(dia1)for the diastolic region according to Equation 3, in operation 640 e,and extract a feature based on T_(dia1) in operation 650 d. On the otherhand, if the apparatus 100 determines that the amplitude P₄ is less thanor equal to the amplitude P₃ in operation 640 c, the apparatus 100 mayextract a feature based on the characteristic point (T₃, P₃).

Alternative to operations 640 c, 640 e, and 650 b, the apparatus 100 maydetermine whether a difference W₁ between the amplitude at a localminimum point T₃ of the second derivative signal 54 and the amplitude ata local maximum point L₄ immediately before T₄ is less than apredetermined threshold, in operation 640 d. In another example, thedifferent W1 may correspond to the difference between the amplitude atT₃ and the amplitude at a local maximum point L₃ immediately before T₄.In operation 640 f, the apparatus 100 may calculate a second internallydividing point T_(dia2) for the diastolic region according to Equation4, and then in operation 650 e, the apparatus 100 may extract a featurebased on the second internally dividing point T_(dia2). However, if theapparatus 100 determines that the difference W₁ is equal to or greaterthan the predetermined threshold in operation 640 d, the apparatus 100may extract a feature based on the characteristic point (T₃, P₃) insteadof the second internally dividing point T_(dia2) in operation 650 f.

Operations 630 a, 640 a, 640 b, 650 a, and 650 b shown in FIG. 6B, andoperations 630 b, 640 c-640 f, and 650 d-650 f shown in FIG. 6c may beperformed in parallel or in sequence.

Then, the apparatus 100 estimates bio-information using the extractedfeatures, in operation 660. In this case, a bio-information estimationmodel may be constructed in advance. The bio-information estimationmodel may be a mathematical equation as shown in Equation 6. When thefeatures are extracted, the apparatus 100 may estimate thebio-information by applying the extracted feature information to thebio-information estimation model.

Then, the apparatus 100 provides a bio-information estimation result tothe user, in operation 670. At this time, the apparatus 100 may providethe estimated bio-information to the user using variousvisual/non-visual methods. In addition, the apparatus 100 may determinethe user's health status based on the estimated bio-information, andprovide warning or an advice on actions to be taken to the useraccording to the determination result.

FIGS. 7A to 7D are diagrams for describing a wearable device accordingto one exemplary embodiment. Various exemplary embodiments of theabove-described apparatus for estimating bio-information may be mountedin a smartwatch or smart band-type wearable device worn on a wrist.However, this is merely an example for convenience of description, andthe exemplary embodiments should not be construed as being limited tobeing applied to a smart watch or smart band-type wearable device.

Referring to FIGS. 7A to 7D, a wearable device 700 includes a devicemain body 710 and a strap 720.

The strap 720 may be configured to be flexible and bent in such a mannerthat is wrapped around the wrist of the user or separated from thewrist. Alternatively, the strap 720 may be configured in a non-separableband form. In this case, the strap 720 may be filled with air or an airbag so as to have elasticity according to a change in pressure appliedto the wrist, and may transmit a pressure change of the wrist to themain body 710.

A battery may be equipped in the main body 710 or the strap 720 tosupply power to the wearable device.

In addition, the wearable device 700 may include, inside the main body710, a measurer 711 configured to measure a bio-signal by emitting lightto an object OBJ and detecting scattered light returning from the objectOBJ, and a processor 712 configured to detect bio-information of theuser using the bio-signal measured by the measurer 711.

The measurer 711 may be mounted on a lower portion of the main body 710,that is, a portion that comes in contact with the object OBJ, forexample, the user's wrist, and may include a light source 711Aconfigured to emit light to the object OBJ and a detector 711Bconfigured to detect light emitted from the object OBJ according to acontrol signal of the processor 712.

In addition, the measurer 711 may further include a contact pressuresensor configured to measure a contact pressure of the object OBJ. Thecontact pressure sensor may measure the contact pressure of the objectOBJ transferred to the main body 710 through the strap 720 that securesthe main body to the object OBJ in a manner that is wrapped around thewrist.

The processor 712 may generate the control signal to control themeasurer 711. In addition, the processor 712 may receive bio-signal datameasured by the measurer 711 and estimate bio-information using thebio-signal data.

For example, the processor 712 may extract a plurality of characteristicpoints from the bio-signal as described above. In this case, theplurality of characteristic points may be extracted from pointsassociated with component pulses of the bio-signal. In addition, a pointwhere the amplitude is the maximum within a predetermined region of thebio-signal or an area of the bio-signal may be extracted ascharacteristic points.

When the plurality of characteristic points are extracted from thebio-signal, the processor 712 may calculate internally dividing pointsof two or more characteristic points and extract features using thecalculated internally dividing points and the characteristic points. Theprocessor 712 may determine characteristic points to be used tocalculate the internally dividing points according to a preset criterionfor calculating the internally dividing points, apply weights to timevalues of two or more determined characteristic points, and calculatethe internally dividing points based on the time values to which theweights are applied. In this case, the weights respectively applied toeach of the time values may be determined based on amplitude values ofeach of the two or more determined characteristic points.

When the contact pressure sensor is equipped in the measurer 711 andmeasures a contact pressure signal of the object, the processor 712 mayguide the user to change the contact pressure applied to the wrist basedon the measured contact pressure signal.

The processor 712 may manage estimated bio-information, for example,blood pressure history information, bio-information used to measurevarious blood pressures, and component pulses decomposed from thebio-information in a storage device. Also, the processor 712 maygenerate additional information, such as alarm or warning informationrelated to estimated bio-information, a change in health status, and thelike, which is necessary for user's healthcare and manage the generatedinformation in the storage device.

In addition, the wearable device 700 may further include an operator 715and a display 714, which are mounted in the main body 710.

The operator 715 may receive a control instruction of the user, transmitthe control instruction to the processor 712, and include a power buttonto enable the user to input an instruction for power on/off of thewearable device 700.

The display 714 may provide a variety of information related to thedetected bio-information under the control of the processor 712. Forexample, the display 714 may display additional information, such asmeasured blood pressure, alarm, or warning information, to the user invarious visual/non-visual ways.

For example, referring to FIGS. 7B and 7C, when blood pressure isestimated according to a user's request, the display 714 may displayestimated blood pressure information as shown in FIG. 7B. Also, when theuser requests detailed information by controlling the operator 715 ortouching the display 714, the display 714 may display the detailedinformation as shown in FIG. 7C. For example, as shown in FIG. 7C, thedisplay 714 may include a first area 714 b and a second area 714 a. Theestimated blood pressure information may be displayed in the first area714 b, as shown in FIG. 7B. Alternatively, as shown in FIG. 7C, thechange in blood pressure may be displayed in the form of a graph.

The display 714 may display a mark M that indicates currently selectedblood pressure information I in the first area 714 b. In FIG. 7C, themark M is shown as a vertical line, but is not limited thereto, and themark M may be displayed in various forms, such as a polygon, such as acircle, a rectangle, and the like, and an arrow indicating a position ofthe selected blood pressure information. When the change in bloodpressure is displayed in the first area 714 b, the user may touch andselect desired blood pressure information or select the desired bloodpressure information by moving the graph to the left and right to alignthe desired blood pressure information to the mark M. When the userselects the blood pressure information in the first area 714 b, bloodpressure information, extracted feature information, and the like may bedisplayed near the selected blood pressure information.

In addition, when the user selects any blood pressure information in thefirst area 714 b, the display 714 may display a bio-signal used toestimate the selected blood pressure information I in response to theuser's selection, and component pulses constituting the bio-signal inthe second area 714 a. In addition, extracted characteristic points maybe displayed on the bio-signal shown in the second area 714 a. By doingso, the user may easily grasp the change of the blood pressure andintuitively understand the bio-signal and a variety of informationextracted from the bio-signal according to the change of the bloodpressure.

In addition, the main body 710 may further include a communicationinterface 713 in an internal space so as to communicate with an externaldevice, such as a portable terminal of the user.

The communication interface 713 may communicate with the external deviceof a user which has a relatively better computing performance andtransmit and receive necessary information under the control of theprocessor 712. For example, the communication interface 713 may receivea request for estimating bio-information from the user's portableterminal. In addition, the communication interface 713 may transmitextracted characteristic points or feature information to the externaldevice to request estimation of bio-information. Further, thecommunication interface 713 may transmit a bio-information estimationresult to the external device so as to be displayed to the user or to beutilized for various purposes, such as bio-information historymanagement and disease research.

While not restricted thereto, an exemplary embodiment can be embodied ascomputer-readable code on a computer-readable recording medium. Thecomputer-readable recording medium is any data storage device that canstore data that can be thereafter read by a computer system. Examples ofthe computer-readable recording medium include read-only memory (ROM),random-access memory (RAM), CD-ROMs, magnetic tapes, floppy disks, andoptical data storage devices. The computer-readable recording medium canalso be distributed over network-coupled computer systems so that thecomputer-readable code is stored and executed in a distributed fashion.Also, an exemplary embodiment may be written as a computer programtransmitted over a computer-readable transmission medium, such as acarrier wave, and received and implemented in general-use orspecial-purpose digital computers that execute the programs. Moreover,it is understood that in exemplary embodiments, one or more units of theabove-described apparatuses and devices can include circuitry, aprocessor, a microprocessor, etc., and may execute a computer programstored in a computer-readable medium.

The foregoing exemplary embodiments are merely exemplary and are not tobe construed as limiting. The present teaching can be readily applied toother types of apparatuses. Also, the description of the exemplaryembodiments is intended to be illustrative, and not to limit the scopeof the claims, and many alternatives, modifications, and variations willbe apparent to those skilled in the art.

What is claimed is:
 1. An apparatus for estimating bio information, theapparatus comprising: a bio-signal acquirer comprising aphotoplethysmogram (PPG) sensor configured to emit a light to an objectand acquire a PPG signal by detecting the light reflected or scatteredfrom the object, or a communication interface configured to receive thePPG signal from an external device; a processor configured to extract aplurality of characteristic points from the PPG signal; apply weightsrespectively to time values of the plurality of characteristic points;determine internally dividing points of the plurality of characteristicpoints based on a sum at the weights; extract feature values from thePPG signal based on the internally dividing points to estimate thebio-information; determine an abnormality of the estimatedbio-information by comparing the estimated bio-information to history ofbio-information estimation of the object; and generate a warning or anadvisory to the object according to the determined abnormality.
 2. Theapparatus of claim 1, wherein the processor is further configured tocalculate the weights based on amplitude values of the plurality ofcharacteristic points.
 3. The apparatus of claim 1, wherein theprocessor is further configured to calculate the weights based ondifferences between first amplitudes at a plurality of points in aderivative signal of the PPG signal and a second amplitude at apredetermined point in the derivative signal, and wherein the pluralityof points in the derivative signal correspond to the plurality ofcharacteristic points extracted from the PPG signal.
 4. The apparatus ofclaim 1, wherein the processor is further configured to estimate thebio-information comprising at least one of blood pressure, vascular age,arterial stiffness, aortic pressure waveform, stress index, and fatiguebased on the extracted feature values.
 5. The apparatus of claim 1,wherein the plurality of characteristic points comprise at least one ofpoints associated with component pulses constituting the PPG signal, anda point at which an amplitude has a maximum value in a systolic regionof the PPG signal.
 6. The apparatus of claim 5, wherein the processor isfurther configured to determine local minimum points in a secondderivative signal of the PPG signal as the points associated with thecomponent pulses.
 7. The apparatus of claim 5, wherein the processor isfurther configured to extract the feature values based on at least oneof a ratio of an area of the PPG signal to an amplitude value at thepoint at which an amplitude has the maximum value in the systolic regionof the PPG signal and a difference in time value between the internallydividing points the PPG signal.
 8. A method of estimatingbio-information, the method comprising: acquiring a bio-signal;extracting a plurality of characteristic points from the bio-signal;applying weights respectively to time values of the plurality ofcharacteristic points; determining internally dividing points of theplurality of characteristic points based on a sum of the weights; andextracting feature values from the bio-signal based on the internallydividing points to estimate the bio-information; determine anabnormality of the estimated bio-information by comparing the estimatedbio-information to history of bio-information estimation of an object;and generate a warning or an advisory to the object according to thedetermined abnormality.
 9. The method of claim 8, wherein thedetermining the internally dividing points comprises calculating theweights based on amplitude values of the plurality of characteristicpoints.
 10. The method of claim 8, wherein the determining theinternally dividing points comprises calculating the weights based ondifferences between first amplitudes at a plurality of points in aderivative signal of the bio-signal and a second amplitude at apredetermined point in the derivative signal, and wherein the pluralityof points in the derivative signal correspond to the plurality ofcharacteristic points extracted from the bio-signal.
 11. The method ofclaim 8, further comprising estimating the bio-information, whichcomprises at least one of blood pressure, vascular age, arterialstiffness, aortic pressure waveform, stress index, and fatigue, based onthe extracted feature values.
 12. The method of claim 8, wherein theplurality of characteristic points comprise at least one of pointsassociated with component pulses constituting the bio-signal, and apoint at which an amplitude has a maximum value in a systolic region ofthe bio-signal.
 13. The method of claim 12, wherein the extracting ofthe characteristic points includes determining local minimum points in asecond derivative signal of the bio-signal as the points associated withthe component pulses.
 14. The method of claim 12, further comprisingextracting the feature values based on at least one of a ratio of anarea of the bio-signal to an amplitude value at the point at which anamplitude has the maximum value in the systolic region of the bio-signaland a difference in time value between the internally dividing points ofthe bio-signal.